刘冰峰,李军,贺佳,师祖姣.基于高光谱植被指数的夏玉米地上干物质量估算模型研究[J].农业机械学报,2016,47(3):254-262.
Liu Bingfeng,Li Jun,He Jia,Shi Zujiao.Estimation Models of Above-ground Dry Matter Accumulation of Summer Maize Based on Hyperspectral Remote Sensing Vegetation Indexes[J].Transactions of the Chinese Society for Agricultural Machinery,2016,47(3):254-262.
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基于高光谱植被指数的夏玉米地上干物质量估算模型研究   [下载全文]
Estimation Models of Above-ground Dry Matter Accumulation of Summer Maize Based on Hyperspectral Remote Sensing Vegetation Indexes   [Download Pdf][in English]
投稿时间:2015-09-08  
DOI:10.6041/j.issn.1000-1298.2016.03.036
中文关键词:  夏玉米  冠层  地上干物质量  高光谱植被指数  估算模型
基金项目:国家高技术研究发展计划(863计划)项目(2013AA102902)和国家自然科学基金项目(31571620、31071374)
作者单位
刘冰峰 西北农林科技大学 
李军 西北农林科技大学 
贺佳 河南省农业科学院 
师祖姣 西北农林科技大学 
中文摘要:2011—2014年连续实施夏玉米长势监测定位实验,在5种不同施氮量、4种不同施磷量和2个夏玉米品种处理下,测定了大喇叭口期、吐丝期、灌浆期和成熟期夏玉米冠层高光谱反射率及对应的地上干物质积累量(Above ground dry matter accumulation, ADMA)。选取了21个光谱植被指数,利用2011年和2013年综合数据进行线性函数、对数函数、二次函数和指数函数模型拟合。在每个生育时期,选择决定系数和F值最高的3个模型,并用2012年和2014年测定光谱数据与地上干物质量对拟合模型进行均方根差和相对误差的验证,选择均方根差和相对误差较小的拟合模型为最适模型。结果表明,在大喇叭口期、吐丝期、灌浆期和成熟期,夏玉米地上干物质量的最佳拟合光谱植被指数分别为GNDVI、PSSRc、NDVI4和DI。
Liu Bingfeng  Li Jun  He Jia  Shi Zujiao
Northwest A&F University,Northwest A&F University,Henan Academy of Agricultural Sciences and Northwest A&F University
Key Words:summer maize  canopy  above ground dry matter accumulation  hyperspectral remote sensing vegetation indexes  estimation model
Abstract:An on site field experiment, which includes five nitrogen fertilizer application rate treatments, four phosphorus fertilizer application rate treatments and two summer maize cultivars treatments, was conducted at agricultural experimental station of Northwest A&F University during 2011—2014. Summer maize canopy spectral reflectance and above ground dry matter accumulation (ADMA) were measured at the huge bellbottom stage, silking stage, filling stage and maturity stage of summer maize. 21 canopy vegetation indexes of hyperspectral remote sensing in 2011 and 2013 were chosen to establish liner, logarithmic, quadratic and exponential regression relationship between ADMA and canopy spectral parameters for each cultivar. Different regression models were applied to establish the relationship between spectrum vegetation indexes and summer maize ADMA. Three models with high coefficients and F values at each growth stage were chosen to verify root mean square error and relative error with data of canopy spectral reflectance and ADMA in 2012 and 2014 separately. The smallest root mean square error and relative error models were chosen as the best models for estimation ADMA of maize. The results show that, at the huge bellbottom stage, filling stage and maturity stage of maize, spectrum vegetation indexes for the best fitting regression relationship models with ADMA were GNDVI, PSSRc, NDVI4 and DI. These models could be used as the best models for the estimation of summer maize above ground ADMA.

Transactions of the Chinese Society for Agriculture Machinery (CSAM), in charged of China Association for Science and Technology (CAST), sponsored by CSAM and Chinese Academy of Agricultural Mechanization Science(CAAMS), started publication in 1957. It is the earliest interdisciplinary journal in Chinese which combines agricultural and engineering. It always closely grasps the development direction of agriculture engineering disciplines and the published papers represent the highest academic level of agriculture engineering in China. Currently, nearly 8,000 papers have been already published. There are around 3,000 papers contributed to the journal each year, but only around 600 of them will be accepted. Transactions of CSAM focuses on a wide range of agricultural machinery, irrigation, electronics, robotics, agro-products engineering, biological energy, agricultural structures and environment and more. Subjects in Transactions of the CSAM have been embodied by many internationally well-known index systems, such as: EI Compendex, CA, CSA, etc.

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